Why the study?
Childhood trauma and dysregulation put youth at risk for psychopathology and altered network-level neural functioning, but few resting-state fMRI studies have examined these links using longitudinal designs.
Do childhood trauma exposure and dysregulation predict changes in resting-state functional networks in youth?
Do childhood trauma exposure and dysregulation predict changes in resting-state functional networks in youth?
Childhood trauma and dysregulation predict altered developmental trajectories of resting-state functional networks in typically developing youth, mirroring patterns seen in clinical populations.
Over the past decade, transdiagnostic indicators in relation to neurobiological processes have provided extensive insight into youth’s risk for psychopathology. During development, exposure to childhood trauma and dysregulation (i.e., so-called AAA symptomology: anxiety, aggression, and attention problems) puts individuals at a disproportionate risk for developing psychopathology and altered network-level neural functioning. Evidence for the latter has emerged from resting-state fMRI studies linking mental health symptoms and aberrations in functional networks (e.g., cognitive control (CCN), default mode networks (DMN)) in youth, although few of these investigations have used longitudinal designs. Herein, we leveraged a three-year longitudinal study to identify whether traumatic exposures and concomitant dysregulation trigger changes in the developmental trajectories of resting-state functional networks involved in cognitive control ( N = 190; 91 females; time 1 M age = 11.81). Findings from latent growth curve analyses revealed that greater trauma exposure predicted increasing connectivity between the CCN and DMN across time. Greater levels of dysregulation predicted reductions in within-network connectivity in the CCN. These findings presented in typically developing youth corroborate connectivity patterns reported in clinical populations, suggesting there is predictive utility in using transdiagnostic indicators to forecast alterations in resting-state networks implicated in psychopathology.
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Picci et al. (2023) studied this question.
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